Parametric Portfolio Policies
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| Author | : Michael W. Brandt |
| Publisher | : |
| Total Pages | : 50 |
| Release | : 2010 |
| Genre | : |
| ISBN | : |
We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return over the sample period. Our approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also provides a new test of the portfolio choice implications of equilibrium asset pricing models. We present an empirical implementation for the universe of all stocks in the CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies.
| Author | : Thomas Gehrig |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2018 |
| Genre | : Loss aversion |
| ISBN | : |
| Author | : Thomas Gehrig |
| Publisher | : |
| Total Pages | : 102 |
| Release | : 2019 |
| Genre | : |
| ISBN | : |
We provide examples of pitfalls for parametric portfolio policies as introduced by Brandt, Santa Clara and Valkanov. For the leading case of constant relative risk aversion (CRRA) strong assumptions on the properties of the returns, the variables used to implement the parametric portfolio policy and the parameter space are necessary to obtain a well defined optimization problem. As possible remedies for practical work various extensions of CRRA Bernoulli utility to the real line are discussed. Also prospect theory is suggested as an alternative approach. We observe that for low levels of relative risk aversion expected utility turns non-monotonic and an interior maximum need not exist. We provide economic conditions that overcome such empirical problems and that guarantee the effectiveness of the approach more broadly. We illustrate our concerns by applying parametric portfolio policies to a large universe of stocks.Full paper is available at: "https://ssrn.com/abstract=3081100" https://ssrn.com/abstract=3081100.
| Author | : Frederik Simon |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023 |
| Genre | : |
| ISBN | : |
We directly optimize portfolio weights as a function of firm characteristics via deep neural networks by generalizing the parametric portfolio policy framework. Our results show that network-based portfolio policies result in an increase of investor utility of between 30 and 100 percent over a comparable linear portfolio policy, depending on whether portfolio restrictions on individual stock weights, short-selling or transaction costs are imposed, and depending on an investor's utility function. We provide extensive model interpretation and show that network-based policies better capture the non-linear relationship between investor utility and firm characteristics. Improvements can be traced to both variable interactions and non-linearity in functional form. Both the linear and the network-based approach agree on the same dominant predictors, namely past return-based firm characteristics.
| Author | : Yunus Emre Ergemen |
| Publisher | : |
| Total Pages | : |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
| Author | : Atdhe Hoxha |
| Publisher | : |
| Total Pages | : |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
| Author | : Stefano Dova |
| Publisher | : |
| Total Pages | : 46 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
This paper extends the parametric portfolio approach by Brandt et al. (2009) to a continuous time setting. I model stocks as call options on firm assets and choose, as characteristics, the three main drivers of stock returns under the structural credit risk model approach: debt maturity, levered asset growth, and asset volatility. I then solve for the parametric portfolio weights to be assigned to these three characteristics in a dynamic setting. I make three contributions: 1) extract characteristics for portfolio allocation from a portfolio of credit-risky single stocks, 2) solve the dynamic programming problem for the parametric portfolio weights, and 3) show that, accounting for credit risk, in a multi-period framework, achieves better Sharpe ratios than naive strategies such as EW and VW as well as comparable Sharpe ratios to those of portfolios built on size, book-to-market, momentum and gross profitability characteristics.
| Author | : Binbin Xu |
| Publisher | : |
| Total Pages | : 142 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
| Author | : Yuliya Plyakha |
| Publisher | : |
| Total Pages | : 40 |
| Release | : 2009 |
| Genre | : |
| ISBN | : |
We study the partial equilibrium portfolio optimization problem for a myopic CRRA investor who can trade options on individual stocks. Applying the parametric portfolio approach of Brandt, Santa-Clara, and Valkanov (forthcoming) to derivatives, we show that options characteristics (such as implied volatility and IV smile skew) convey information about the mispricing in the option portfolios. We take the data on all US-traded options to build characteristic-based factor portfolios of options. An investor uses them in addition to the market portfolio and Fama and French (1992) factors in her utility maximization. Surprisingly, portfolios based on the IV smile skew turn out to be less important than IV-based portfolios, and factor portfolios from call options are in general more interesting for an investor than the factors from puts. Market frictions in the form of stock shortsale constraints are compensated by the use of options, and having options with no stock shortsales allowed may be better than having only stocks with shortsales permitted. Monthly rebalancing leads to extreme transaction costs for an investor facing the full bid-ask spread, providing limits to arbitrage interpretation of the documented mispricing in the option portfolios.
| Author | : Michael W. Brandt |
| Publisher | : |
| Total Pages | : 68 |
| Release | : 2004 |
| Genre | : Portfolio management |
| ISBN | : |
"We propose a novel approach to optimizing portfolios with large numbers of assets. We model directly the portfolio weight in each asset as a function of the asset's characteristics. The coefficients of this function are found by optimizing the investor's average utility of the portfolio's return over the sample period. Our approach is computationally simple, easily modified and extended, produces sensible portfolio weights, and offers robust performance in and out of sample. In contrast, the traditional approach of first modeling the joint distribution of returns and then solving for the corresponding optimal portfolio weights is not only difficult to implement for a large number of assets but also yields notoriously noisy and unstable results. Our approach also provides a new test of the portfolio choice implications of equilibrium asset pricing models. We present an empirical implementation for the universe of all stocks in the CRSP-Compustat dataset, exploiting the size, value, and momentum anomalies"--National Bureau of Economic Research web site.
